How to Use the Guance Cloud / 观测云 MCP in AutoGen

Q: Can AutoGen agents collaborate to solve a Guance Cloud / 观测云 incident?

Yes, one agent can fetch events using listevents while another queries the underlying metrics with querydata. They share this context to diagnose the issue.

Q: How does the server protect my Guance Cloud workspace billing data?

Billing information retrieved via getbilling is processed strictly in-memory within a zero-trust V8 sandbox. No telemetry data or financial metrics are ever persisted or exposed to external third parties.

Let your AutoGen agents debate system health and cross-verify incident root causes using Guance Cloud telemetry via this MCP Server.

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Connect Guance Cloud / 观测云 MCP to AutoGen

Create your Vinkius account to connect Guance Cloud / 观测云 to AutoGen and route execution through our secure gateway. The platform manages server hosting, runtime updates, and security layers. Configuration requires no manual server provisioning.

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Setup Guance Cloud / 观测云 with AutoGen

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Multi-agent debate on active incident response

A security agent uses `list_access_keys` to verify compliance while a triage agent runs `list_events` to find active system anomalies. The agents debate whether an event is a security breach or a simple resource bottleneck. They negotiate the best response using live data. One agent checks `get_event` for details, while another queries historical performance with `query_data`, converging on a verified solution before alerting your team.

Audit MCP Server monitors via agent consensus

This MCP Server exposes monitor configurations to your agent cluster through `list_monitors`. A performance agent evaluates whether your current thresholds are too loose, while a budget agent analyzes costs. They pull details using `get_monitor` and compare them with workspace limits from `get_workspace`. The agents collaborate to propose optimized configurations, ensuring your alerts stay sharp without causing alert fatigue.

Coordinate dashboard and log source verification

One agent uses `list_dashboards` to check your visual layouts, while another calls `list_log_sources` to ensure logs are flowing correctly. Together, they confirm whether your observability pipeline is fully operational. If a log source is missing, the agents flag the gap. By combining multiple specialized agents, you get a continuous, automated audit of your Guance Cloud workspace setup.

Setup guide

Set up Guance Cloud / 观测云 MCP in AutoGen

Prerequisites

Python 3.10+ installed
autogen-ext[mcp] package
Active Vinkius subscription with a valid endpoint token

1

Install AutoGen with MCP
Run pip install "autogen-ext[mcp]" autogen-agentchat. The MCP extension includes mcp_server_tools for stateless tool access.
2

Fetch tools from the MCP
Call mcp_server_tools(SseServerParams(url=...)) with your Vinkius endpoint. Replace [YOUR_TOKEN_HERE] with your token from cloud.vinkius.com.
3

Run your agent
Pass the tools to AssistantAgent and call agent.run(). The agent invokes Guance Cloud / 观测云 tools and returns structured results.

agent.py

from autogen_ext.tools.mcp import SseServerParams, mcp_server_tools
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

tools = await mcp_server_tools(server_params)

agent = AssistantAgent(
    name="Guance Cloud / 观测云_assistant",
    model_client=OpenAIChatCompletionClient(model="gpt-4o"),
    tools=tools,
)

result = await agent.run("List recent Guance Cloud / 观测云 data")
print(result.messages[-1].content)

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Prerequisites

Python 3.10+ installed
autogen-ext[mcp] + autogen-agentchat
Active Vinkius subscription with a valid endpoint token

1

Install dependencies
Same packages as above. McpWorkbench is ideal when your agent needs stateful sessions across multiple tool calls.
2

Use McpWorkbench as context manager
Wrap your agent in async with McpWorkbench(...) to maintain shared state and resources. The workbench manages the full MCP session lifecycle.
3

Run with workbench
Pass workbench=workbench to your agent. State is preserved across multiple tool calls within the same session.

agent.py

from autogen_ext.tools.mcp import McpWorkbench, SseServerParams
from autogen_agentchat.agents import AssistantAgent
from autogen_ext.models.openai import OpenAIChatCompletionClient

server_params = SseServerParams(
    url="https://edge.vinkius.com/[YOUR_TOKEN_HERE]/mcp"
)

async with McpWorkbench(server_params) as workbench:
    agent = AssistantAgent(
        name="Guance Cloud / 观测云_assistant",
        model_client=OpenAIChatCompletionClient(model="gpt-4o"),
        workbench=workbench,
    )

    result = await agent.run("List recent Guance Cloud / 观测云 data")
    print(result.messages[-1].content)

Get your connection token →

Independent Platform Disclaimer: Vinkius is an independent platform and is not affiliated with, endorsed by, sponsored by, verified by, or otherwise authorized by Guance Cloud / 观测云. All third-party trademarks, logos, and brand names are the property of their respective owners. Their use on this website is strictly for informational purposes to identify service compatibility and interoperability.

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Common questions about Guance Cloud / 观测云 MCP in AutoGen

Use the autogen-ext package to load the tools via the MCP adapter. You can then pass the resulting tool list directly to your AssistantAgent constructor.

Yes, one agent can fetch events using `list_events` while another queries the underlying metrics with `query_data`. They share this context to diagnose the issue.

You can assign a dedicated security agent to monitor tool usage. This agent checks tools like `list_access_keys` to ensure compliance before any action is taken.

The integration supports both stdio and Streamable HTTP transports. This lets you connect to your managed server instance directly.

Billing information retrieved via `get_billing` is processed strictly in-memory within a zero-trust V8 sandbox. No telemetry data or financial metrics are ever persisted or exposed to external third parties.

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